It is known to use a classifier to identify an object of interest in an image. Classifiers attempting to identify an object in images where the object varies in appearance, for example due to distortion, may suffer reduced performance or failure where the variation is too high.
Examples of publications in relevant technical fields include:
Vinyals, Oriol, et al. “Learning with recursive perceptual representations.” Advances in Neural Information Processing Systems. 2012;
Bingham, Ella, and Heikki Mannila. “Random projection in dimensionality reduction: applications to image and text data.” Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2001; and
Paul, Saurabh, et al. “Random Projections for Support Vector Machines.” AISTATS. Vol. 3. 2013.
It is desirable to provide a method of processing an image for generating an object classification model that is less susceptible to variation in an objects appearance when classifying the object.